How does NetApp use AI in healthcare and what infrastructure challenges do data scientists face?
Answered at 11:19 in IoT Trojectory Podcast - Episode 19 - Interview with Esteban Rubens - Healthcare AI · IoT Trajectory Podcast Series
How does NetApp use AI in healthcare and what infrastructure challenges do data scientists face?
NetApp enables the right infrastructure to make the job of data scientists easier by providing data management solutions. Deep learning in healthcare requires a lot of labeled data to train models. However, data scientists spend 75 to 90 percent of their time on data preparation, data cleansing, normalization, data movement, and data mining rather than actual data science work. This is often caused by not having the right infrastructure, such as data silos. NetApp works as one leg of a three-legged infrastructure stool alongside compute from NVIDIA and fast networking like 100 gigabit per second networking to solve these challenges.
Full answer and detailsRead the whole answer, key facts and every other question from this episode
In short
NetApp enables the right infrastructure to make the job of data scientists easier by providing data management solutions.
Esteban Rubens, Leader for the Healthcare AI Practice at NetApp · IoT Trojectory Podcast - Episode 19 - Interview with Esteban Rubens - Healthcare AI · IoT Trajectory Podcast Series · answer at 11:19
Key takeaways
- NetApp enables the right infrastructure to make the job of data scientists easier by providing data management solutions.
Quote to remember
“We want to help people get to the point in which they can do their jobs. We want to remove frustration from the process.”
— Esteban Rubens
The full answer · about 4 min
NetApp enables the right infrastructure to make the job of data scientists easier by providing data management solutions. Deep learning in healthcare requires a lot of labeled data to train models. However, data scientists spend 75 to 90 percent of their time on data preparation, data cleansing, normalization, data movement, and data mining rather than actual data science work. This is often caused by not having the right infrastructure, such as data silos. NetApp works as one leg of a three-legged infrastructure stool alongside compute from NVIDIA and fast networking like 100 gigabit per second networking to solve these challenges.
Key facts
- Data scientists spend 75 to 90 percent of their time on data preparation and non-science-specific tasks
- Clinical staff can receive a sepsis warning four to six hours before a patient experiences sepsis using deep learning models
- Readmission risk can potentially be reduced by 80 percent in some cases by keeping patients in hospital one to two days longer
- Healthcare industry experiences widespread clinical staff burnout across North America, Western Europe, and Asia
- 100 gigabit per second networking is now available for healthcare AI infrastructure projects